Artificial Intelligence Literacy and Responsible Use of Generative AI among Undergraduate Students
Keywords:
artificial intelligence literacy, generative AI, higher education, academic integrity, digital literacy, responsible technology useAbstract
The rapid expansion of generative artificial intelligence has created new opportunities and challenges for higher education. University students increasingly use artificial intelligence tools to generate ideas, summarize information, improve language, prepare study materials, and obtain explanations of difficult concepts. However, effective use of these tools requires more than technical familiarity. Students must also understand the limitations of artificial intelligence, evaluate the reliability of generated information, protect personal data, and use such technologies in accordance with academic integrity principles.
This study examined the relationship between artificial intelligence literacy and the responsible use of generative artificial intelligence among undergraduate students. A descriptive correlational research design was used with a simulated sample of 120 undergraduate students from four academic faculties. Data were collected through an artificial intelligence literacy questionnaire, a responsible-use scale, and a short scenario-based evaluation task. The simulated findings indicated that students demonstrated moderate practical familiarity with generative artificial intelligence but weaker understanding of algorithmic limitations, data privacy, source verification, and ethical use. Artificial intelligence literacy was positively associated with responsible use. Students who reported higher levels of AI literacy were more likely to verify generated information, acknowledge AI assistance, avoid submitting unedited AI-generated work, and consider privacy risks.
The findings suggest that artificial intelligence literacy should be incorporated into university curricula through explicit instruction, practical activities, academic integrity guidance, and critical evaluation tasks. The data in this article are fictional and have been prepared exclusively for website design, journal formatting, and demonstration purposes.
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